Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. This line graph are plotted many points.
An introduction to Matplotlib.
| index | type |
|---|---|
| 1 | matplotlib |
| 2 | plotly |
| 3 | seaborn |
import matplotlib.pyplot as plt
fig, ax = plt.subplots() # Create a figure containing a single axes.
ax.plot([1, 2, 3, 4,5], [1, 4, 10, 3,-15]) # Plot some data on the axes.
[<matplotlib.lines.Line2D at 0x1993448e090>]
Plotly's Python graphing library makes interactive, publication-quality graphs. This graph is scatter plots. Scatter plots with variable-sized circular markers are often known as bubble charts.
An introduction to Plotly.
import plotly.express as px
import plotly
plotly.offline.init_notebook_mode()
df = px.data.iris()
fig = px.scatter(df, x="sepal_width", y="sepal_length", color="species",
size='petal_length', hover_data=['petal_width'])
fig.show()
Seaborn is a library for making statistical graphics in Python. This graph shows how the signal changes depending on the timepoint. (statistical estimation)
An introduction to Seaborn.
import seaborn as sns
sns.set_theme(style="darkgrid")
# Load an example dataset with long-form data
fmri = sns.load_dataset("fmri")
# Plot the responses for different events and regions
sns.lineplot(x="timepoint", y="signal",
hue="region", style="event",
data=fmri)
<Axes: xlabel='timepoint', ylabel='signal'>
